Abstract

Hydrologic extremes such as floods and droughts are often spatially related, which increases management challenges and potential impacts. However, these spatial relationships in high and low flows are often overlooked in risk assessments and we know little about their differences and origins. Her... Show moreHydrologic extremes such as floods and droughts are often spatially related, which increases management challenges and potential impacts. However, these spatial relationships in high and low flows are often overlooked in risk assessments and we know little about their differences and origins. Here, we ask how spatial relationships of both types of hydrologic extremes and their potential hydro-meteorological drivers differ and vary by season. We propose lagged upper- and lower-tail correlation as a measure of extremal dependence for temporally ordered events to build complex networks of high and low flows. We compare complex networks of overall, low and high flows, determine hydro-meteorological drivers of these networks, and map past changes in spatial relationships using a large-sample data set in Central Europe. Our network comparison shows that low flows are correlated more strongly and over longer distances than high flows and high- and low-flow networks are strongest in spring and weakest in summer. Our driver analysis shows that high-flow dependence is most strongly governed by precipitation in winter and evapotranspiration in summer while low-flow dependence is most strongly governed by snowmelt in winter and evapotranspiration in fall. Finally, our change analysis shows that changes in connectedness (i.e., the number of catchments a catchments shows strong flow correlations with) vary spatially and are mostly positive for high flows. We conclude that spatial flow correlations are considerable for both high and particularly low flows as a result of a combination of spatially related hydro-meteorological drivers whose importance varies by extreme type and season. Show less